Technical Product Lead - Equity and Multi-Asset Indices

About the role

LSEG is looking for a versatile, technical product lead for its FTSE Russell Equities Product, Research & Design team. You will own product outcomes across the Equity and Multi-Asset index offering while shaping the direction of a new in-house AI tool built within Research, moving between index product work and hands-on technical product leadership. The role sits in London with the Research team, co-located and fast-paced.

Key responsibilities

• Drive product strategy and roadmap across the Equity and Multi-Asset index offering and the AI tool, aligned to global and regional priorities.
• Collect and categorise feedback from the AI tool's users (internal today, external as it scales) and turn it into a prioritised feature roadmap, working with Research developers to ship.
• Engage clients and run market and competitive analysis to spot demand and growth opportunities, translating requirements into index enhancements and new solutions.
• Make pragmatic prioritisation calls at speed, balancing client demand, technical effort and commercial value.
• Partner with Sales and Marketing on positioning, go-to-market and revenue growth across institutional and wealth segments.
• Bridge the engineers building the AI tool and the people who rely on it, keeping senior collaborators updated on progress.

Required profile

• Genuine product-led attitude, starting from the user and the problem and owning outcomes rather than tasks.
• Proven ability to thrive in fast-paced, ambiguous environments, deciding quickly and reprioritising; able to switch context and pick up unfamiliar topics fast.
• 5+ years in product, technical product or research roles, ideally in financial services or the index/data industry; familiarity with equity and/or multi-asset products, indices and benchmarks (ETFs, funds, derivatives).
• Degree in Finance, Economics, Engineering, Mathematics, Computer Science or a related field; a CFA or relevant technical/AI credential is an advantage.

Required skills

• Technical fluency to work credibly with software and AI/ML developers; no need to write production code, but understanding how AI products are built and shipped.
• Experience supporting a software or data product, ideally AI/ML.
• Strong feedback synthesis and prioritisation instincts, and the ability to say no and defend trade-offs.
• Strong analytical and communication skills, working across research, technology, sales, operations and marketing.
• Advantage: Python coding, familiarity with data science workflows and comfort using frontier AI tools.